This disclosure relates generally to calibration of sensors on vehicles, for example, autonomous vehicles, and more particularly to calibration of lidar and camera sensors of installed on vehicles.
Autonomous vehicles, also known as self-driving cars, driverless cars, auto, or robotic cars, drive from a source location to a destination location without requiring a human driver to control and navigate the vehicle. Automation of driving is difficult due to several reasons. For example, autonomous vehicles use sensors to make driving decisions on the fly, but vehicle sensors cannot observe everything all the time. Vehicle sensors can be obscured by corners, rolling hills, and other vehicles. Vehicles sensors may not observe certain things early enough to make decisions. In addition, lanes and signs may be missing on the road or knocked over or hidden by bushes, and therefore not detectable by sensors. Furthermore, road signs for rights of way may not be readily visible for determining from where vehicles could be coming, or for swerving or moving out of a lane in an emergency or when there is a stopped obstacle that must be passed.
Autonomous vehicles can use map data to figure out some of the above information instead of relying on sensor data. However conventional maps have several drawbacks that make them difficult to use for an autonomous vehicle. For example maps do not provide the level of accuracy required for safe navigation (e.g., 10 cm or less). GPS systems provide accuracies of approximately 3-5 meters, but have large error conditions resulting in an accuracy of over 100 m. This makes it challenging to accurately determine the location of the vehicle.
Autonomous vehicles use various processes for self-driving based on high definition maps generated using data obtained from multiple sensors, for example, lidar and camera sensors. Each sensor of the autonomous vehicle, may use its own coordinate system. For example, the lidar may use one coordinate system and a camera may use another coordinate system. If the coordinate systems used by two different sensors are not calibrated together, any processing that combines data from the two sensors is likely to be inaccurate. Furthermore, the calibration parameters of various sensors of autonomous vehicles drift over time. Conventional techniques require manual processing by experts, thereby requiring autonomous vehicles to be provided to the experts for calibration. Such techniques are time consuming and expensive. Furthermore, these techniques put burden on the users of the vehicles by requiring them to arrive at a specialized facility for calibration or to perform technical steps on their own for performing calibration.